PullCoVapart

Antiviral strategies targeting replication machineries have proven their efficacy, with as gold example the cure of HCV patients and to a lesser extent the HIV treatments that control viral load. One of the prerequisites is a detailed knowledge of the structure and function of the multi-protein replication complexes. The genome of coronaviruses (CoV) is a positive-sense, single-stranded RNA, the largest among (+)RNA viruses (~30-kb) and paradoxically with a higher genetic stability in comparison with others. It is now established that it is the 3'-5' exonuclease activity encoded by CoVs that allows correction of misincorporations during viral replication. This proofreading activity explains, in part, the lack of effect of ribavirin on patients infected with SARS-CoV or MERS-CoV. Thus, future anti-CoV strategies will have to integrate this unique property for (+)RNA viruses. This proposal relies on solid results obtained for SARS-CoV and will combine methods in artificial intelligence with protein biochemistry to propose therapeutic options. More specifically, it aims to (1) Reconstitute, in vitro, the replicative core machine of COVID-19; (2) Through this in vitro system, inhibitors from two classes will be sought. A new class of natural nucleotide chain terminators from bacterial anti-phage defense will be tested, in collaboration with Pantheon Biosciences company. VHH camel antibodies (named nanobodies) against the COVID-19 nsp8 protein will be generated. Preventing the nsp8 interaction with the RNA polymerase will hamper viral replication. Moreover, due to the nsp8 sequence conservation among the viral family, a pan-CoV inhibitor can be expected. To maximize the effect, a multi-valent nanobody will be gathered. Interestingly, inhalation of nebulized nanobody as route of administration is possible; and finally, (3) Model in silico the COVID-19 RNA polymerase, paving the way toward anticipation of the COVID-19 RNA polymerase behavior in relation to inhibitors. Indeed, the models to be developed in this project will be designed to be coupled, in the future, with other simulation models, developed from the results of objective (2). In the long-term, this second generation of models will evaluate in silico the efficiency of those potential antivirals. This interdisciplinary project will allow, in a short time frame, the acquisition of knowledge, as well the development of a system to screen molecules against the COVID-19, which will be accessible to the entire scientific community.